Early assessment of the relationship between the COVID-19 pandemic and births in high-income countries.

Drawing on past pandemics, scholars have suggested that the COVID-19 pandemic will bring about fertility decline. Evidence from actual birth data has so far been scarce. This brief report uses data on vital statistics from a selection of high-income countries, including the United States. The pandemic has been accompanied by a significant drop in crude birth rates beyond that predicted by past trends in 7 out of the 22 countries considered, with particularly strong declines in southern Europe: Italy (-9.1%), Spain (-8.4%), and Portugal (-6.6%). Substantial heterogeneities are, however, observed.

Deconstructing bias in social preferences reveals groupy and not-groupy behavior.

Group divisions are a continual feature of human history, with biases toward people's own groups shown in both experimental and natural settings. Using a within-subject design, this paper deconstructs group biases to find significant and robust individual differences; some individuals consistently respond to group divisions, while others do not. We examined individual behavior in two treatments in which subjects make pairwise decisions that determine own and others' incomes. In a political treatment, which divided subjects into groups based on their political leanings, political party members showed more in-group bias than Independents who professed the same political opinions. However, this greater bias was also present in a minimal group treatment, showing that stronger group identification was not the driver of higher favoritism in the political setting. Analyzing individual choices across the experiment, we categorize participants as "groupy" or "not groupy," such that groupy participants have social preferences that change for in-group and out-group recipients, while not-groupy participants' preferences do not change across group context. Demonstrating further that the group identity of the recipient mattered less to their choices, strongly not-groupy subjects made allocation decisions faster. We conclude that observed in-group biases build on a foundation of heterogeneity in individual groupiness.

The Methuselah Effect: The Pernicious Impact of Unreported Deaths on Old-Age Mortality Estimates.

We examine inferences about old-age mortality that arise when researchers use survey data matched to death records. We show that even small rates of failure to match respondents can lead to substantial bias in the measurement of mortality rates at older ages. This type of measurement error is consequential for three strands in the demographic literature: (1) the deceleration in mortality rates at old ages; (2) the black-white mortality crossover; and (3) the relatively low rate of old-age mortality among Hispanics, often called the "Hispanic paradox." Using the National Longitudinal Survey of Older Men matched to death records in both the U.S. Vital Statistics system and the Social Security Death Index, we demonstrate that even small rates of missing mortality matching plausibly lead to an appearance of mortality deceleration when none exists and can generate a spurious black-white mortality crossover. We confirm these findings using data from the National Health Interview Survey matched to the U.S. Vital Statistics system, a data set known as the "gold standard" (Cowper et al. 2002) for estimating age-specific mortality. Moreover, with these data, we show that the Hispanic paradox is also plausibly explained by a similar undercount.

Credit scores, cardiovascular disease risk, and human capital.

Credit scores are the most widely used instruments to assess whether or not a person is a financial risk. Credit scoring has been so successful that it has expanded beyond lending and into our everyday lives, even to inform how insurers evaluate our health. The pervasive application of credit scoring has outpaced knowledge about why credit scores are such useful indicators of individual behavior. Here we test if the same factors that lead to poor credit scores also lead to poor health. Following the Dunedin (New Zealand) Longitudinal Study cohort of 1,037 study members, we examined the association between credit scores and cardiovascular disease risk and the underlying factors that account for this association. We find that credit scores are negatively correlated with cardiovascular disease risk. Variation in household income was not sufficient to account for this association. Rather, individual differences in human capital factors­educational attainment, cognitive ability, and self-control­predicted both credit scores and cardiovascular disease risk and accounted for ∼45% of the correlation between credit scores and cardiovascular disease risk. Tracing human capital factors back to their childhood antecedents revealed that the characteristic attitudes, behaviors, and competencies children develop in their first decade of life account for a significant portion (∼22%) of the link between credit scores and cardiovascular disease risk at midlife. We discuss the implications of these findings for policy debates about data privacy, financial literacy, and early childhood interventions.

Combining forward and backward mortality estimation.

Demographers often form estimates by combining information from two data sources-a challenging problem when one or both data sources are incomplete. A classic example entails the construction of death probabilities, which requires death counts for the subpopulations under study and corresponding base population estimates. Approaches typically entail 'back projection', as in Wrigley and Schofield's seminal analysis of historical English data, or 'inverse' or 'forward projection' as used by Lee in his important reanalysis of that work, both published in the 1980s. Our paper shows how forward and backward approaches can be optimally combined, using a generalized method of moments (GMM) framework. We apply the method to the estimation of death probabilities for relatively small subpopulations within the United States (men born 1930-39 by state of birth by birth cohort by race), combining data from vital statistics records and census samples.

The Impact of the Great Migration on Mortality of African Americans: Evidence from the Deep South.

The Great Migration-the massive migration of African Americans out of the rural South to largely urban locations in the North, Midwest, and West-was a landmark event in U.S. HISTORY: Our paper shows that this migration increased mortality of African Americans born in the early twentieth century South. This inference comes from an analysis that uses proximity of birthplace to railroad lines as an instrument for migration.

Tooth loss in Appalachia and the Mississippi delta relative to other regions in the United States, 1999-2010.

OBJECTIVES: We examined regional variation in tooth loss in the United States from 1999 to 2010. METHODS: We used 6 waves of the Behavioral Risk Factor Surveillance System and data on county characteristics to describe regional trends in tooth loss and decompose diverging trends into the parts explained by individual and county components. RESULTS: Appalachia and the Mississippi Delta had higher levels of tooth loss than the rest of the country in 1999. From 1999 to 2010, tooth loss declined in the United States. However, Appalachia did not converge toward the US average, and the Mississippi Delta worsened relative to the United States. Socioeconomic status explained the largest portion of differences between regions in 1999, but a smaller portion of the trends. The Mississippi Delta is aging more quickly than the rest of the country, which explains 17% of the disparity in the time trend. CONCLUSIONS: The disadvantage in tooth loss is persistent in Appalachia and growing in the Mississippi Delta. The increasing disparity is partly explained by changes in the age structure but is also associated with behavioral and environmental factors.

Measuring Cognitive Function and Cognitive Decline with Response Time Data in NSHAP.

OBJECTIVES: Scholarly, clinical, and policy interest in cognitive function has grown over the last several decades in part due to large increases in Alzheimer's Disease and related dementias as populations age. However, adequate measures of cognitive function have not been available in many research data sets. We argue that a wealth of previously unexploited survey data exists to model cognition and cognitive decline. METHODS: We use metadata of the time it takes older respondents in the National Social Life, Health and Aging Survey, which we label response times (RT), to answer questions in a standard cognitive assessment. We compare several measures of RT to a survey-adapted form of the Montreal Cognitive Assessment (MoCA). RESULTS: We show that RT predict both concurrent and future MoCA scores. Our results show that longer and more varied RT at baseline predict lower MoCA scores five year later, net of baseline scores and controls. We also show that the effect of RT measures on predicting current MoCA differ for individuals of different races and ages, but are not different by gender. DISCUSSION: Our paper demonstrates that RT constitute a separate powerful measure of cognitive functioning. RT may be remarkably useful both to clinicians and social scientists because they can increase accuracy of cognitive assessment without increasing the time it takes to administer the assessment.

Exploring the Racial Divide in Education and the Labor Market through Evidence from Interracial Families.

We examine gaps between minorities and whites in education and labor market outcomes, controlling for many covariates including maternal race. Identification comes from different reported races within the family. Estimates show two distinct patterns. First, there are no significant differences in outcomes between black and white males with white mothers. Second, large differences persist between these groups and black males with black mothers. The patterns are insensitive to alternative measures of own race and school fixed effects. Our results suggest that discrimination is not occurring on the basis of child skin color but through mother-child channels such as dialect or parenting practices.

The Impact of Economic Conditions on Participation in Disability Programs: Evidence from the Coal Boom and Bust.

We examine the impact of the coal boom of the 1970's and the coal bust of the 1980's on disability program participation. These shocks provide clear evidence that as the value of labor-market participation increases, disability program participation falls. For the Disability Insurance program, the elasticity of payments with respect to local earnings is between -0.3 and -0.4 and for Supplemental Security Income the elasticity is between -0.4 and -0.7. Consistent with a model where qualifying for disability programs is costly, the relationship between economic conditions and program participation is much stronger for permanent than for transitory economic shocks.

Workplace concentration of immigrants.

Casual observation suggests that in most U.S. urban labor markets, immigrants have more immigrant coworkers than native-born workers do. While seeming obvious, this excess tendency to work together has not been precisely measured, nor have its sources been quantified. Using matched employer-employee data from the U.S. Census Bureau Longitudinal Employer-Household Dynamics (LEHD) database on a set of metropolitan statistical areas (MSAs) with substantial immigrant populations, we find that, on average, 37 % of an immigrant's coworkers are themselves immigrants; in contrast, only 14 % of a native-born worker's coworkers are immigrants. We decompose this difference into the probability of working with compatriots versus with immigrants from other source countries. Using human capital, employer, and location characteristics, we narrow the mechanisms that might explain immigrant concentration. We find that industry, language, and residential segregation collectively explain almost all the excess tendency to work with immigrants from other source countries, but they have limited power to explain work with compatriots. This large unexplained compatriot component suggests an important role for unmeasured country-specific factors, such as social networks.

THE ROLE OF LOCATION IN EVALUATING RACIAL WAGE DISPARITY.

A standard object of empirical analysis in labor economics is a modified Mincer wage function in which an individual's log wage is specified to be a function of education, experience, and an indicator variable identifying race. We analyze this approach in a context in which individuals live and work in different locations (and thus face different housing prices and wages). Our model provides a justification for the traditional approach, but with the important caveat that the regression should include location-specific fixed effects. Empirical analyses of men in U.S. labor markets demonstrate that failure to condition on location causes us to (i) overstate the decline in black-white wage disparity over the past 60 years, and (ii) understate racial and ethnic wage gaps that remain after taking into account measured cognitive skill differences that emerge when workers are young.

Are Children "Normal"?

We examine Becker's (1960) contention that children are "normal." For the cross section of non-Hispanic white married couples in the U.S., we show that when we restrict comparisons to similarly-educated women living in similarly-expensive locations, completed fertility is positively correlated with the husband's income. The empirical evidence is consistent with children being "normal." In an effort to show causal effects, we analyze the localized impact on fertility of the mid-1970s increase in world energy prices - an exogenous shock that substantially increased men's incomes in the Appalachian coal-mining region. Empirical evidence for that population indicates that fertility increases in men's income.

An economic model of amniocentesis choice.

Medical practitioners typically utilize the following protocol when advising pregnant women about testing for the possibility of genetic disorders with their fetus: Pregnant women over the age of 35 should be tested for Down syndrome and other genetic disorders, while for younger women, such tests are discouraged (or not discussed) as the test can cause a pregnancy to miscarry. The logic appears compelling. The rate at which amniocentesis causes a pregnancy to miscarry is constant while the rate of genetic disorder rises substantially over a woman's reproductive years. Hence the potential benefit from testing - being able to terminate a fetus that is known to have a genetic disorder - rises with maternal age. This article argues that this logic is incomplete. While the benefits to testing do rise with age, the costs rise as well. Undergoing an amniocentesis always entails the risk of inducing a miscarriage of a healthy fetus. However, these costs are lower at early ages, because there is a higher probability of being able to replace a miscarried fetus with a healthy birth at a later age. We develop and calibrate a dynamic model of amniocentesis choice to explore this tradeoff. For parameters that characterize realistic age patterns of chromosomal abnormalities, fertility rates and miscarriages following amniocentesis, our model implies a falling, rather than rising, rate of amniocentesis as women approach menopause.

Gender Wage Disparities among the Highly Educated.

In the U.S. college-educated women earn approximately 30 percent less than their non-Hispanic white male counterparts. We conduct an empirical examination of this wage disparity for four groups of women-non-Hispanic white, black, Hispanic, and Asian-using the National Survey of College Graduates, a large data set that provides unusually detailed information on higher-level education. Nonparametric matching analysis indicates that among men and women who speak English at home, between 44 and 73 percent of the gender wage gaps are accounted for by such pre-market factors as highest degree and major. When we restrict attention further to women who have "high labor force attachment" (i.e., work experience that is similar to male comparables) we account for 54 to 99 percent of gender wage gaps. Our nonparametric approach differs from familiar regression-based decompositions, so for the sake of comparison we conduct parametric analyses as well. Inferences drawn from these latter decompositions can be quite misleading.

Explaining Family Change and Variation: Challenges for Family Demographers.

Twenty years ago, the National Institute of Child Health and Human Development (NICHD) issued a request for proposals that resulted in the National Survey of Families and Households (NSFH), a unique survey valuable to a wide range of family scholars. This paper describes the efforts of an interdisciplinary group of family demographers to build on the progress enabled by the NSFH and many other theoretical and methodological innovations. Our work, also supported by NICHD, will develop plans for research and data collection to address the central question of what causes family change and variation. We outline the group's initial assessments of orienting frameworks, key aspects of family life to study, and theoretical and methodological challenges for research on family change. Finally, we invite family scholars to follow our progress and to help develop this shared public good.